code: def test_validation_unsupported():
      """
      Makes sure we raise a proper message to the user,
      when providing not supported data input
      """
      validator = InputValidator()
      with pytest.raises(
          ValueError, match=r"Inconsistent number of train datapoints.*"
      ):
          validator.fit(
              X_train=np.array([[0, 1, 0], [0, 1, 1]]),
              y_train=np.array([0, 1, 0, 0, 0, 0]),
          )
      with pytest.raises(
          ValueError, match=r"Inconsistent number of test datapoints.*"
      ):
          validator.fit(
              X_train=np.array([[0, 1, 0], [0, 1, 1]]),
              y_train=np.array([0, 1]),
              X_test=np.array([[0, 1, 0], [0, 1, 1]]),
              y_test=np.array([0, 1, 0, 0, 0, 0]),
          )
      with pytest.raises(
          ValueError,
          match=r"Cannot call transform on a validator .*fitted",
      ):
          validator.transform(
              X=np.array([[0, 1, 0], [0, 1, 1]]),
              y=np.array([0, 1]),
          )
  
file_path: auto-sklearn/test/test_data/test_validation.py
imports: import numpy
  import pandas
  import sklearn.datasets
  import sklearn.model_selection
  from scipy import sparse
  from autosklearn.data.validation import InputValidator
  import pytest
label_desc: Use image node_id 4 for calling a global function with example usage: test_validation_unsupported() without return types